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News
May 20, 2026
HSE University Opens First Representative Office of Satellite Laboratory in Brazil
HSE University-St Petersburg opened a representative office of the Satellite Laboratory on Social Entrepreneurship at the University of Campinas in Brazil. The platform is going to unite research and educational projects in the spheres of sustainable development, communications and social innovations.
May 18, 2026
The 'Second Shift' Is Not Why Women Avoid News
Women are more likely than men to avoid political and economic news, but the reasons for this behaviour are linked less to structural inequality or family-related stress than to personal attitudes and the emotional perception of news content. This conclusion was reached by HSE researchers after analysing data from a large-scale survey of more than 10,000 residents across 61 regions of Russia. The study findings have been published in Woman in Russian Society.
May 15, 2026
Preserving Rationality in a Period of Turbulence
The HSE International Laboratory for Logic, Linguistics and Formal Philosophy studies logic and rationality in a transformed world characterised by a diversity of logical systems and rational agents. The laboratory supports and develops academic ties with Russian and international partners. The HSE News Service spoke with the head of the laboratory, Prof. Elena Dragalina-Chernaya, about its work.

 

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Machine learning in prediction of stock market indicators based on historical data and data from Twitter sentiment analysis.

Ch. 9.3. P. 440–444.
Porshnev A., Redkin I. E., Shevchenko A. V.

Development of linguistic technologies and penetration of social media provide powerful possibilities to investigate users’ moods and psychological states of people. In this paper we discussed possibility to improve accuracy of stock market indicators predictions by using data about psychological states of Twitter users. For analysis of psychological states we used lexicon-based approach, which allow us to evaluate presence of eight basic emotions in more than 755 million tweets. The application of Support Vectors Machine and Neural Networks algorithms to predict DJIA and S&P500 indicators are discussed.

Language: English
Full text
Keywords: нейронные сетиметод опорных векторовmoodneural networkspsychological states of internet userstwitterсоциальные настроенияSupport Vector Machineтвиттерstock market indicatorиндексы фондового рынка

In book

2013 IEEE 13th International Conference on Data Mining Workshops
Los Alamitos: IEEE Computer Society, 2013.
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